Data Analytics Applications in Animal Health Bio-Technology

Data Analytics is the next phase in the evolutionary data cycle. Today, decades worth of data may be quickly processed to provide insights into the veterinary industry. From identifying the roots of a problem to providing data-rich remedies, data analytics can accomplish much. Animal health is a sector that utilizes the most complex processes and is intensely data-rich. Getting quick, detailed, and accurate reports on animal health related topics a game-changer.

BIOTECH TYPES

Red Biotech: the research and creation of medicinal and veterinary products

Yellow Biotech: the production and provision of food

Green Biotech: transgenics and genetic modifications

Blue Biotech: use and exploitation of marine-based resources

White Biotech: waste reductive industrial manufacturing

While we will provide a short overview of what each of these entails, the focus of this article isn’t an extensive exposition of the topics. Rather we will be delving into the use of data analytics in each sub-field. However, knowing each category is vital to understanding data analytics’ role in improving the former’s performance. So here is a great site for a summary of what each of the above entails: https://builtin.com/biotech

DATA ANALYTICS TYPES

Descriptive: the condition of the business

Diagnostic: the root cause behind the descriptive.

Predictive: future trends based on past trends

Prescriptive: what to do based on the current situation and future likelihoods.

Cognitive: combining intelligent technologies like AI, MLA, and Deep Learning to perform tasks or functions.

Again, we don’t have the space to detail each of these and although you might get a good idea of what they refer to based on the context of their usage in the article, you deserve a proper resource. So, here’s a more elaborate source to help you easily understand: https://www.weirdgeek.com/2018/11/types-of-analytics/

APPLICATIONS of DATA ANALYTICS

There is a myriad of new applications of data analytics in every field in animal health and biotechnology. We, however, aim to explore the most interesting in each of the above genres of biotechnology.

Red Biotech: the research and creation of medicinal and veterinary products

Red Biotech is by far the most common and has the greatest number of applications so don’t panic when you see the size of this section. The rest won’t be as extensive, we promise.

Mining scientific journals, medical records, and clinical trial data is the first step. Predictive analytics can then be used to improve decision-making by highlighting relevant factors. This accelerates the rate of drug discovery while lowering the cost and raising the efficacy of control studies and treatment trials.

Because drugs aren’t personalized, they often have irregular side effects. A highly accurate way to prescribe drugs could be made possible by prescriptive analytics. Complex data sequences and heterogenous data sets can be sorted by interactions to find drugs or treatment options tailored to the patient’s unique needs. This would yield not just what drug would be ideal, but the time, sequence, and dosage that would suit you. This is known as precision medicine.

Learning analytics can measure the cost vs value discrepancy in training programs. But that’s just the tip of the iceberg for analytics, really. Measuring each staff member’s level of training is determined based on the level of proficiency, time-to-competency, the complexity of the subject matter, etc. Data Analytics can monitor their rate of application or the effectiveness of practice. Using their response data coupled with feedback patterns, it can then strengthen the training program. All this requires barely any human intervention or monitoring.

Combing through the genomic sequences and EHRs can offer many advantages. Livestock feed additive suppliers and animal health research and development companies could benefit from being able to monitor the precise risk of infection (using QRMA, e.g.), disease outbreaks among herds, and develop targeted drug series for groups with similar symptoms or features.

Furthermore, internet sources can also be utilized for risk management. Dr. Ed Tucker, VP of Janssen Research & Development put it best in an interview with MIT Sloan Management Review. He says, “You can do what’s called Internet “scrapes” of information, where you draw down lots of various hits or posts from the Internet, and then analyze that data. You can listen to the chat essentially, the public sentiment, in the virtual environment.” https://sloanreview.mit.edu/article/how-pharmaceuticals-can-avoid-the-side-effects-of-social-media/

Yellow Biotech: production of food

Biotech is applied to the animal feed industry in terms of output, nutritional value, preservation, early maturation, etc. Commercial farms often have issues in foreseeing disastrous natural events. Climate does not follow the same trends as a consequence of climate change and hence both food growers and livestock rearers face more weather anomalies than usual. This makes maintaining the optimal conditions and balancing the nutrient intake levels for particular cattle breeds – such as Black Angus, Simmental, and Hereford – more complicated.

Technology such as soil sensors and weather trackers now provide access to crop yields, weather data, fertilization, soil and pasture quality, and erosion over some time, etc. Analysis of these factors can then be implemented to identify undesirable plant genes for rDNA erasure. Predictive analysis can also be applied to weather data to help prepare for environmental upheavals and capitalize on opportunities. Analytics software can further pinpoint waste management methods to aid environmentally sensitive agribusinesses.

Blue Biotech: the use and exploitation of marine-based resources

The global consumption of seafood is growing every year. By 2030 it is predicted to rise by as much as 20% annually and most of this protein is sourced from the ocean. Alongside the consistent rise of ocean exploitation is the rise of marine pollution, 80% of which is caused by land-based waste. These threaten our marine ecology as well as our future source of food. Part of the issue with sustainably keeping up with seafood demand is that the fishing industry does not currently practice precision fishing.

Precision fishing uses sophisticated sensing and tracking technology to monitor the size and location of shoals. This forecast would cover an extensive area and offer a variety of options. Fishing companies can then use data on the status of fish stock, shoal growth rate, fleet size, quantity and value of landing, etc. to help determine the responsible pursuit of certain schools. Ship operators and navigators could make data analytics-powered navigation decisions for optimal outcomes in storms and periods of turbulence.

Fault detection systems can also inform operators about maintenance needs and ship performance to reduce or manage risk. These advanced systems could also propose potential energy-efficiency improvement methods based on the calculation and verification of ships’ carbon emissions.

Green Biotech: transgenics and genetic modifications

The Genomic branch handles massive data sets which were traditionally manually sifted through to glean insights. This was usually a long and arduous process. It also contains the field of genetic modification – the selection and transfer of certain stretches of DNA from one organism to another. The issue is that results aren’t always predictable and outside variables could lead to a lack of conclusiveness. That is, until genetic modification met data analyticscv.

Most geneticists now have greater access to the concurrent analysis of multiple genes. Data analytics also play a part in Next Generation Sequencing (NGS), which is the mass sequencing of genes used to detect mutations. In this way, analysis allows for a more accurate diagnosis of disorders that involve a great deal of genetic diversity. The interpretation of results is also much more straightforward now, which makes it easier to decide on the best course of action.

White Biotech: waste reductive industrial manufacturing

White biotech uses biomaterial such as microorganisms and enzymes to produce sustainable materials and products such as biofuels and bioplastics. It also aims to produce industrial components in a waste-minimizing manner. The aim is to optimize production practices to make them energy efficient. 

Using type and origin data on different waste amassment points, companies can assess their material sourcing. Data analysis could find correlations between environmental management problems and available bio-solution technologies. It can also identify further profitable applications for the designs and fibers based on demand study.

CHALLENGES WITH DATA ANALYTICS  

The overarching concern with Big Data is well known: privacy.

Giving large corporations unfiltered access to our personal information as well as permission to collect further information is the equivalent of having an observer live in your house.

The controversy is amplified, however, when you include health data. Farm owners can be hesitant to publicly expose the dietary and health information of their livestock to researchers for fear of information leaks. Furthermore, participants in clinical studies may consent to the review and publishing of the overall results, but not to giving individual firms access to their personal medical reports.

Technically, the data is already available and all this new capability does is interpret it. But this software could come to unpredictable conclusions that some clients might prefer remained unknown.